The subject matter disclosed herein relates generally to image reconstruction, and more particularly to systems and methods for remote image reconstruction.
Images of a subject, for example aspects of interest of a patient, may be obtained by a variety of different methods. Such methods include, as examples, single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT). These imaging systems typically form an image by performing one or more data acquisitions at discrete time intervals, with an image formed from a combination of the information obtained by the data acquisitions. For example, nuclear medicine (NM) imaging systems use one or more image detectors to acquire imaging data, such as gamma ray or photon imaging data. The image detectors may be, for example, gamma cameras that acquire a view or views of emitted radionuclides (from an injected radioisotope) from a patient being imaged.
After the imaging data is acquired, one or more processing steps are performed to reconstruct an image using the imaging data. This processing may be quite intensive in nature, and may require significant processing capability. Conventional processing systems are located proximate to the image acquisition site. For example, a processor or workstation typically is associated with an operator's console or other unit and dedicated to a particular image acquisition device. Thus, conventional scanning and reconstructing of images require considerable resources expended for the hardware required on-site for each dedicated workstation with processing capabilities. Further, such systems are often difficult and inconvenient to update. For example, each time a software update is to be implemented (for example, to update or otherwise change the software for reconstructing images), the software must be uploaded on-site in field, requiring the expense and inconvenience of using a field technician, as well as resulting in downtime of the processor and associated scanning equipment during the update. Also, each time software is updated for a particular console or workstation, a costly and timely regulatory approval process must be performed for the particular software and device combination. For example, the approval process may be required for each particular storage and device type combination. By updating the software for such a combination, the entire operating software of the device is essentially updated, and regulatory approval for the updated particular storage and device type combination is required. Further still, due at least in part to limited storage as well as difficulty in updating, and the initial expense associated with acquiring a given software product for image reconstruction, current systems typically provide a very limited range of options of software available for processing, thereby limiting different types and/or levels of detail of processing available for a given imaging device. Yet further still, typical on-site consoles are generally configured to only accept a limited amount of software, and compatibility issues prevent certain consoles (for example, from a first manufacturer or provider) from utilizing certain software (for example, from a second manufacturer or provider). Thus, certain presently known image reconstruction systems or methods are difficult to update, limited in performance, and require costly equipment, both in terms of initial purchase and also in terms of maintenance and updating.